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Energy and GHG emissions management of agricultural systems using multi objective particle swarm optimization algorithm: a case study

journal contribution
posted on 2023-05-19, 21:37 authored by Barak, S, Yousefi, M, Maghsoudlou, H, Jahangiri, S
In the recent centuries, one of the most important ongoing challenges is energy consumption and its environmental impacts. As far as agriculture is concerned, it has a key role in the world economics and a great amount of energy from different sources is used in this sector. Since researchers have reported a high degree of inefficiency in developing countries, it is necessary for the modern management of cropping systems to have all factors (economics, energy and environment) in the decision-making process simultaneously. Therefore, the aim of this study is to apply Multi-Objective Particle Swarm Optimization (MOPSO) to analyze management system of an agricultural production. As well as MOPSO, two other optimization algorithm were used for comparing the results. Eventually, Taguchi method with metrics analysis was used to tune the algorithms’ parameters and choose the best algorithms. Watermelon production in Kerman province was considered as a case study. On average, the three multi-objective evolutionary algorithms could reduce about 30 % of the average Greenhouse Gas (GHG) emissions in watermelon production although as well as this reduction, output energy and benefit cost ratio were increased about 20 and 30 %, respectively. Also, the metrics comparison analysis determined that MOPSO provided better modeling and optimization results.


Publication title

Stochastic Environmental Research and Risk Assessment











Place of publication

175 Fifth Ave, New York, USA, Ny, 10010

Rights statement

Copyright 2015 Springer-Verlag Berlin Heidelberg

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  • Restricted

Socio-economic Objectives

Environmentally sustainable energy activities not elsewhere classified

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